Abstract

This paper estimates the wage returns to training, paying careful attention to the choice
of functional form. Both the National Longitudinal Survey of Youth (NLSY) and
Employer Opportunity Pilot Project (EOPP) datasets indicate that the return to
an extra hour of formal training diminishes sharply with the amount of
training received. A cube root specification fits the data best, but the log
specification also does well. The linear and quadratic specifications
substantially understate the effect of training.

If wages are not adjusted continuously, estimating the total effect of training requires
that one include lagged and lead training as well as current training in the
regression equation. Consequently, the NLSY is ideally suited to estimate the
total return to training. We find very large returns to formal training.
These returns are sharply reduced when one adjusts for heterogeneity in wage
growth. Returns are reduced further when one takes into account the effect of
promotions and the fact that direct costs are a substantial portion of the
total cost of training. The mixed continuous-discrete nature of the training
variable means that measurement error can cause estimates of the effects of
short spells of training to be biased upward, but we demonstrate that the
maximum upward bias in estimated returns at the geometric mean is relatively
small.

After correcting for confounding factors, we are left with a return to training that
is several times the returns to schooling. Heterogeneity in returns explains
how returns to formal training can be so high while most workers do not get
formal training. In the EOPP data, the return to training is significantly
higher in more complex jobs. With unobserved heterogeneity in returns, our
estimates can be regarded as the return to training for the trained, but
cannot be extrapolated to the untrained.